
import os
import sys
import unittest


SCREAMING_SNAKE_CASE				:int									=							os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
SCREAMING_SNAKE_CASE				:Dict									=							os.path.join(git_repo_path, 'src', 'transformers')

SCREAMING_SNAKE_CASE				:Any									=							'\n{0} = None\n'

SCREAMING_SNAKE_CASE				:Tuple									=							'\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n'


SCREAMING_SNAKE_CASE				:Optional[Any]									=							'\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n'





class 				UpperCAmelCase (    unittest.TestCase    ):




	'''simple docstring'''





	def 							UpperCamelCase_    (			self   :					Optional[int]					):
					__A       =					find_backend("    _import_structure[\"models.albert\"].append(\"AlbertTokenizerFast\")"					)
					self.assertIsNone(A					)

					__A       =					find_backend("    if not is_tokenizers_available():"					)
					self.assertEqual(A				,"tokenizers"					)

					__A       =					find_backend("    if not is_tensorflow_text_available():"					)
					self.assertEqual(A				,"tensorflow_text"					)

					__A       =					find_backend("    if not (is_sentencepiece_available() and is_tokenizers_available()):"					)
					self.assertEqual(A				,"sentencepiece_and_tokenizers"					)

					__A       =					find_backend(
					    "    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"					)
					self.assertEqual(A				,"sentencepiece_and_tensorflow_text"					)

					__A       =					find_backend(
					    "    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):"					)
					self.assertEqual(A				,"sentencepiece_and_tokenizers_and_vision"					)






	def 							UpperCamelCase_    (			self   :					List[str]					):
					__A       =					read_init()
					# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
					self.assertIn("torch"				,A					)
					self.assertIn("tensorflow_text"				,A					)
					self.assertIn("sentencepiece_and_tokenizers"				,A					)

					# Likewise, we can't assert on the exact content of a key
					self.assertIn("BertModel"				,objects["torch"]					)
					self.assertIn("TFBertModel"				,objects["tf"]					)
					self.assertIn("FlaxBertModel"				,objects["flax"]					)
					self.assertIn("BertModel"				,objects["torch"]					)
					self.assertIn("TFBertTokenizer"				,objects["tensorflow_text"]					)
					self.assertIn("convert_slow_tokenizer"				,objects["sentencepiece_and_tokenizers"]					)






	def 							UpperCamelCase_    (			self   :					Union[str, Any]					):
					__A       =					create_dummy_object("CONSTANT"				,"'torch'"					)
					self.assertEqual(A				,"\nCONSTANT = None\n"					)

					__A       =					create_dummy_object("function"				,"'torch'"					)
					self.assertEqual(
					    A				,"\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"					)

					__A       =					"\nclass FakeClass(metaclass=DummyObject):\n    _backends = 'torch'\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, 'torch')\n"
					__A       =					create_dummy_object("FakeClass"				,"'torch'"					)
					self.assertEqual(A				,A					)







	def 							UpperCamelCase_    (			self   :					List[Any]					):
					__A       =					"# This file is autogenerated by the command `make fix-copies`, do not edit.\nfrom ..utils import DummyObject, requires_backends\n\n\nCONSTANT = None\n\n\ndef function(*args, **kwargs):\n    requires_backends(function, [\"torch\"])\n\n\nclass FakeClass(metaclass=DummyObject):\n    _backends = [\"torch\"]\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, [\"torch\"])\n"
					__A       =					create_dummy_files({"torch": ["CONSTANT", "function", "FakeClass"]}					)
					self.assertEqual(dummy_files["torch"]				,A					)






'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


lowerCAmelCase_     						=				{}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase_     						=				['''GPTSw3Tokenizer''']


if TYPE_CHECKING:
    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_gpt_swa import GPTSwaTokenizer

else:
    import sys

    lowerCAmelCase_     						=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


